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Recommendations for the validation of immunoassays used for detection of host antibodies against biotechnology products

https://doi.org/10.1016/j.jpba.2008.09.020Get rights and content

Abstract

Most biological drug products elicit some level of anti-drug antibody (ADA) response. This antibody response can, in some cases, lead to potentially serious side effects and/or loss of efficacy. In humans, ADA often causes no detectable clinical effects, but in the instances of some therapeutic proteins these antibodies have been shown to cause a variety of clinical consequences ranging from relatively mild to serious adverse events. In nonclinical (preclinical) studies, ADA can affect drug exposure, complicating the interpretation of the toxicity, pharmacokinetic (PK) and pharmacodynamic (PD) data. Therefore, the immunogenicity of therapeutic proteins is a concern for clinicians, manufacturers and regulatory agencies.

In order to assess the immunogenic potential of biological drug molecules, and be able to correlate laboratory results with clinical events, it is important to develop reliable laboratory test methods that provide valid assessments of antibody responses in both nonclinical and clinical studies. For this, method validation is considered important, and is a necessary bioanalytical component of drug marketing authorization applications. Existing regulatory guidance documents dealing with the validation of methods address immunoassays in a limited manner, and in particular lack information on the validation of immunogenicity methods. Hence this article provides scientific recommendations for the validation of ADA immunoassays. Unique validation performance characteristics are addressed in addition to those provided in existing regulatory documents pertaining to bioanalyses. The authors recommend experimental and statistical approaches for the validation of immunoassay performance characteristics; these recommendations should be considered as examples of best practice and are intended to foster a more unified approach to antibody testing across the biopharmaceutical industry.

Introduction

Biopharmaceutical products differ from conventional small molecule drugs in that they are larger in size (i.e., typically >1–3 kDa), are biopolymers of amino acids, carbohydrates or nucleic acids, and are often manufactured by human or non-human cells or microorganisms. Because of these differences, biopharmaceuticals have a greater potential for inducing immune responses [1], [2]. The immunogenic potential of a biopharmaceutical is governed by product-intrinsic factors (e.g., species-specific epitopes, degree of foreignness, glycosylation status, extent of aggregation or denaturation, impurities and formulation), product-extrinsic factors (e.g., route of administration, acute or chronic dosing, pharmacokinetics, and existence of endogenous equivalents), and patient-specific factors (e.g., autoimmune disease, immunosuppression, and replacement therapy) [3].

While often benign, the induction of anti-drug antibodies (ADA) can result in adverse clinical sequelae including hypersensitivity or autoimmunity, and altered pharmacokinetics (for example, drug neutralization, abnormal biodistribution, or enhanced drug clearance rates, potentially resulting in altered efficacy of the treatment). Immune response caused by drug treatment is, therefore, a major safety and efficacy concern for regulatory agencies, drug manufacturers, clinicians, and patients [4]. Consequently, the United States Food & Drug Administration (FDA) as well as regulatory authorities in the European Union, Canada, Japan and Australia require that ADA be evaluated and correlated with any pharmacological and/or toxicological observations [5], [6], [7].

Correlations between immunogenicity and clinical sequelae depend on an objective detection and characterization of antibodies against biological therapeutics in nonclinical and clinical studies. Hence bioanalytical methods used for immunogenicity testing should be properly developed and validated before testing is initiated with study samples. Recommendations on method development and optimization [8], [9] and strategies for the detection and characterization of ADA are provided in prior publications [10], [11]. Validation is defined as a process of demonstrating, through the use of specific laboratory investigations, that the performance characteristics of an analytical method are suitable for its intended analytical use [12], [13]. In the case of ADA detection methods, validation constitutes proof that the assay will reliably (i.e., consistently and reproducibly) detect low amounts of drug-specific antibodies in a complex biological matrix, such as serum or plasma. Validation should be performed in the ‘pre-study’ phase (i.e., before clinical or nonclinical study samples are analyzed), but it is equally important to demonstrate that the assay remains valid or ‘in control’, during the ‘in-study’ phase (i.e., when clinical or nonclinical study samples are analyzed) as well; only then can the results of test samples be deemed acceptable.

The intent of this paper is to present the performance characteristics important for the validation of ADA immunoassays and to recommend appropriate and objective methodological approaches of validation. The recommendations in this paper should be considered as examples of best practice; alternate methodological approaches may also be acceptable, as long as scientific rationale and objectivity are maintained and uncompromised irrespective of assay-specific practical considerations. It is advised that the acceptability of alternative approaches be discussed with regulatory authorities. Cellular function-based neutralizing ADA (NAb) bioassays and assays for cell-mediated immune responses are outside the scope of this paper.

Section snippets

ADA detection

Clinical and nonclinical immunogenicity is generally evaluated via detection and characterization of treatment-induced ADA. A number of analytical formats and detection methods are available for the detection of ADA, including enzyme-linked immunosorbent assay (ELISA), radioimmunoassay (RIA) or radioimmunoprecipitation assay (RIPA), surface plasmon resonance (SPR), and electrochemiluminescence (ECL). Each of these formats has its relative merits and limitations, and these have been discussed in

Pre-study assay validation

The validation of an assay before commencing sample bioanalysis for nonclinical or clinical studies is called ‘pre-study validation’; it describes in mathematical and quantifiable terms the performance characteristics of an assay [8]. This should not be confused with the colloquial term “prevalidation” used to describe any preparatory work performed before initiating pre-study validation. On the other hand, in-study validation refers to the monitoring of assay performance throughout its use to

In-study validation (monitoring) and assay revalidation

In-study validation (monitoring for maintenance of system suitability) and revalidation are critical components of any bioanalytical method. Hence, the validation of a method actually does not end until the method is ultimately retired from analytical use.

For in-study performance of quantitative bioanalytical methods, acceptance criteria for precision and accuracy are generally required [13]. Since accuracy is not applicable for ADA methods, monitoring the performance of quality control

Conclusion

The first of three papers in this series on immunogenicity evaluation described common approaches for developing and optimizing immunoassays for antibodies to biotechnology products [8], following which the second paper described strategies for the evaluation of ADAs [10]. This paper described assay performance characteristics that are important to ADA immunoassay validation, and provided recommendations on objective approaches for determining them. These are intended to facilitate a

Acknowledgements

This work was sponsored by The Ligand Binding Assay Bioanalytical Focus Group (LBABFG) of the American Association of Pharmaceutical Scientists (AAPS).

A draft of this manuscript was presented in a Round Table session at the 2007 AAPS National Biotechnology Conference on June 26th, 2007, in San Diego, U.S.A. The finalized version was presented in a Round table session at the 2008 AAPS National Biotechnology Conference on June 24th, 2008, in Toronto, Canada. The authors thank the numerous

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